
Secoda is an AI-powered platform for efficient data management and utilization.
Secoda is an AI-powered data management platform that provides a comprehensive solution for data discovery, cataloging, lineage, and documentation. It helps analytics engineers and modern data teams to efficiently search, understand, and utilize their data.
Secoda is an AI-powered platform for efficient data management and utilization.
To use Secoda, sign up for an account and log in. Once logged in, you can connect your data sources to Secoda through integrations with various data warehouses and BI tools. After connecting your data sources, you can explore and search your data using AI-powered contextual search. Additionally, you can generate documentation, create data requests, analyze data, manage access control, and collaborate with team members.
Secoda's data portal improves data literacy, enables faster onboarding to data, and provides better visibility and governance of data.
Yes, Secoda has an API for various functionalities such as documentation, catalog, lineage, and more.
Yes, Secoda integrates with Okta and Active Directory for managing permissions and access control.
Secoda integrates with Snowflake, Big Query, Redshift, Databricks, Postgres, Oracle, Microsoft SQL, MySQL, and S3.
Secoda integrates with Tableau, Looker, Metabase, Redash, Mode, Sigma, Power BI, and Google Data Studio.
Yes, Secoda works with both dbt Cloud and Core, bringing in YAML file information, tests, tags, metrics, and column level lineage.
Secoda automates column and table level data lineage, along with tests, events, and ETL lineage. Users can also contribute to lineage manually using the API.
Secoda doesn't have native data monitoring or quality features, but it can integrate with tools like great expectations and dbt tests for data monitoring within the lineage UI.
Yes, Secoda integrates with Git and provides version control for all changes made in Secoda, allowing rollbacks and easy review of workspace changes.
Secoda extracts metadata about your data, including resource names, popularity, lineage, queries, descriptions, and frequent usage.